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@radekosmulski
Created July 22, 2022 03:02
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "6c8bde99",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Fri Jul 22 02:30:39 2022 \n",
"+-----------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 510.73.08 Driver Version: 510.73.08 CUDA Version: 11.6 |\n",
"|-------------------------------+----------------------+----------------------+\n",
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
"| | | MIG M. |\n",
"|===============================+======================+======================|\n",
"| 0 Quadro RTX 8000 Off | 00000000:08:00.0 Off | Off |\n",
"| 33% 29C P8 24W / 260W | 1MiB / 49152MiB | 0% Default |\n",
"| | | N/A |\n",
"+-------------------------------+----------------------+----------------------+\n",
" \n",
"+-----------------------------------------------------------------------------+\n",
"| Processes: |\n",
"| GPU GI CI PID Type Process name GPU Memory |\n",
"| ID ID Usage |\n",
"|=============================================================================|\n",
"| No running processes found |\n",
"+-----------------------------------------------------------------------------+\n"
]
}
],
"source": [
"!nvidia-smi"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d0f8e962",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"source": [
"import torch\n",
"from torchvision.models import resnet50\n",
"import matplotlib.pyplot as plt\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "61f3b1b0",
"metadata": {},
"outputs": [],
"source": [
"model = resnet50(False)\n",
"img = torch.randn(1,3,224,224)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "9c33c573",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 407 ms, sys: 0 ns, total: 407 ms\n",
"Wall time: 34.1 ms\n"
]
}
],
"source": [
"%%time\n",
"\n",
"_ = model(img)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "a65cfada",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"30.891056398649198"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"start = time.perf_counter()\n",
"\n",
"n_inf = 100\n",
"for i in range(n_inf):\n",
" _ = model(img)\n",
" \n",
"end = time.perf_counter()\n",
"n_inf / (end - start)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "2ee376f9",
"metadata": {},
"outputs": [],
"source": [
"def batch_of_images(batch_size):\n",
" return torch.randn(batch_size,3,224,224)\n",
"\n",
"def runtime_in_seconds(f, *args, move_to_GPU=False, num_runs=1):\n",
" start = time.perf_counter()\n",
" for _ in range(num_runs):\n",
" if move_to_GPU: args = [arg.cuda() for arg in args]\n",
" f(*args)\n",
" end = time.perf_counter()\n",
" return end - start"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "3e1e6f9e",
"metadata": {},
"outputs": [],
"source": [
"runtimes = []\n",
"\n",
"for batch_size in range(128):\n",
" runtimes.append(\n",
" runtime_in_seconds(model, batch_of_images(batch_size))\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "faefb5f0",
"metadata": {},
"outputs": [],
"source": [
"runtimes_cpu_sequential = []\n",
"\n",
"for batch_size in range(128):\n",
" runtimes_cpu_sequential.append(\n",
" runtime_in_seconds(model, batch_of_images(1), num_runs=batch_size)\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "5e64a684",
"metadata": {},
"outputs": [],
"source": [
"model = model.cuda()\n",
"img = torch.randn(1,3,224,224).cuda()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "86f0de96",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 8.05 ms, sys: 528 µs, total: 8.58 ms\n",
"Wall time: 7.66 ms\n"
]
}
],
"source": [
"%%time\n",
"\n",
"_ = model(img)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "d9cb11cf",
"metadata": {},
"outputs": [],
"source": [
"runtimes_gpu = []\n",
"\n",
"for batch_size in range(128):\n",
" runtimes_gpu.append(\n",
" # no cheating here\n",
" # I am including the time it takes to move data to the GPU in the calculation\n",
" runtime_in_seconds(model, batch_of_images(batch_size), move_to_GPU=True)\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "f90a1494",
"metadata": {},
"outputs": [],
"source": [
"runtimes_gpu_sequential = []\n",
"\n",
"for batch_size in range(128):\n",
" runtimes_gpu_sequential.append(\n",
" # no cheating here\n",
" # I am including the time it takes to move data to the GPU in the calculation\n",
" runtime_in_seconds(model, batch_of_images(1), move_to_GPU=True, num_runs=batch_size)\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "0f700df5",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x360 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import matplotlib\n",
"matplotlib.rcParams.update({'font.size': 16})\n",
"\n",
"plt.subplots(1,2, figsize=(20,5))\n",
"plt.subplot(1,2,1)\n",
"plt.plot(runtimes, label='inference on CPU')\n",
"plt.plot(runtimes_gpu, label='inference on GPU')\n",
"plt.legend()\n",
"plt.ylabel('time [s]')\n",
"plt.xlabel('batch size')\n",
"plt.suptitle('Inference time vs batch size')\n",
"plt.title('Batch inference -- CPU vs GPU')\n",
"\n",
"plt.subplot(1,2,2)\n",
"plt.plot(runtimes_gpu, label='batch inference on GPU')\n",
"plt.plot(runtimes_gpu_sequential, label='sequential inference on GPU')\n",
"plt.ylabel('time [s]')\n",
"plt.xlabel('num images')\n",
"plt.legend()\n",
"plt.title('Inference on the GPU -- sequential vs batch')\n",
"\n",
"plt.tight_layout()"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "1c82794e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 0.98, 'Sequential inference time -- CPU vs GPU')"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(runtimes_cpu_sequential, label='inference on CPU')\n",
"plt.plot(runtimes_gpu_sequential, label='inference on GPU')\n",
"plt.legend()\n",
"plt.ylabel('time [s]')\n",
"plt.xlabel('num images')\n",
"plt.suptitle('Sequential inference time -- CPU vs GPU')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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